Designing, building and operating AI that delivers real-world impact
Responsible AI
Taking good care of your AI applications
Responsible use of AI is essential for organizations that want to benefit from the advantages of generative AI. CEOs worldwide see that investments in AI lead to higher profits and more efficient work processes, but they also recognize the challenges, such as strict regulations and the need for proper integration with existing systems and data platforms. The integration of AI has become necessary for organisations to maintain their competitive positions and the possibilities of AI are growing daily as systems become more autonomous and operate in an increasingly intelligent way. Therefore, it is crucial that AI is used in a safe and accountable manner. This is what we call ‘Responsible AI’.
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Trust through Responsible AI
Companies are increasingly faced with tough questions:
Do you know where your organization actually stands on Responsible AI — or are you operating on assumptions?
Do your AI tools and systems comply with GDPR and EU AI Act requirements - have you identified and classified all your AI systems by risk level as the EU AI Act requires?
Do you have a clear AI governance framework in place with defined roles, accountability and escalation paths?
Are your internal AI policies translating into real, day-to-day practices — or do they just exist on paper?
Are your high-risk AI systems meeting the transparency, documentation and human oversight requirements that regulation demands?
Can you provide independent assurance that your AI systems are ethical, fair and trustworthy or are you marking your own homework?
Are you protecting your customers' and stakeholders' fundamental rights in practice — not just in your privacy notice?
Once your AI systems are live, are you continuously monitoring them for drift, bias and performance, or do you deploy and forget?
Your answers should begin and end with Responsible AI.
Organizations go through multiple steps before fully embracing Responsible AI
How we help you govern your Responsible AI at scale
Establish robust AI Governance across the AI System Lifecycle
Classify, document and monitor AI models in line with the EU AI Act
We help organisations design and implement AI governance frameworks — including roles, accountability structures, and oversight mechanisms — aligned with the EU AI Act, ISO/IEC 42001, and NIST AI RMF. We support AI teams in classifying AI systems under EU AI Act risk categories, maintaining a central AI inventory, and documenting models across their lifecycle — ensuring traceability, auditability, and continuous oversight from development through deployment and retirement.
Our services include:
- AI Governance Framework Design
- AI Systems Classification & Inventory
- Lifecycle Documentation & Traceability
- AI Governance Platform Selection & Implementation
AI Governance Framework Design
Design and implementation of end-to-end AI governance structures — including roles, accountability, decision-making authority, escalation paths and human oversight mechanisms — aligned with ISO/IEC 42001, NIST AI RMF and the EU AI Act.
AI Systems Classification & Inventory
Identification and classification of AI systems under EU AI Act risk categories, establishment of a centralized AI inventory, and ongoing mapping of AI use cases across the organisation.
Lifecycle Documentation & Traceability
Documentation standards across the full AI model lifecycle — from design and development through deployment and retirement — ensuring traceability, reproducibility and audit-readiness at every stage.
AI Governance Platform Selection & Implementation
Evaluation, selection and implementation of AI governance platforms to operationalize your governance framework — enabling centralized inventory management, automated risk classification, policy enforcement, monitoring and regulatory reporting in a single pane of glass.
Identify, assess and mitigate AI‑related risks
Embed AI risk management and security controls by design
Assurance over AI is the set of processes, controls, and independent checks used to ensure AI systems are trustworthy, accurate, secure, and compliant with laws and ethics. It covers how AI is designed, trained, tested, monitored, and governed, so stakeholders can have confidence that the system works as intended and manages risks such as bias, misuse, and unintended outcomes.
Our services include:
- Proactive / Program Assurance over AI development & Deployment standards
- AI Regulatory Readiness
- AI Risk Management & Controls Assurance
- Model Risk Management (MRM) Review
- Data Governance for AI
- Data Bias Audits
- AI Audit Readiness & Supervisory Support
Proactive / Program Assurance over AI development & Deployment standards
Independent assurance over whether AI development and deployment activities adhere to defined standards, policies, and governance requirements, assessing consistency, control design, and oversight without participating in system design or implementation.
AI Regulatory Readiness
Independent review of the bank’s AI regulatory preparedness, including assessment of EU AI Act readiness, and AI‑related privacy considerations.
AI Risk Management & Controls Assurance
Assurance over the design and operating effectiveness of AI risk management and control frameworks, focusing on risk identification, monitoring, escalation, and oversight based on the responsible AI principles.
Model Risk Management (MRM) Review
Independent review of AI/ML model governance and model risk management practices, including governance arrangements, documentation, explainability and transparency mechanisms, and fairness and ethical risk considerations.
Data Governance for AI
Assessment of data governance practices supporting AI use, focusing on data ownership, quality management, lineage, access controls, and accountability frameworks.
Data Bias Audits
Independent assessment of processes and controls in place to identify, monitor, and address data bias risks within AI ecosystems.
AI Audit Readiness & Supervisory Support
Independent evaluations to support readiness for audit and supervisory scrutiny, including AI audit‑readiness assessments and ISO42001 readiness.
Design AI policies and compliance frameworks you can rely on
Translate regulation into practical, operational guidance
We work with Legal and Compliance teams to design AI policies, governance standards and compliance frameworks aligned with the EU AI Act and broader regulatory requirements. Our approach ensures legal clarity, consistent interpretation of obligations, and defensible compliance across AI use cases and vendors.
Our services include:
- EU AI Act Compliance & Readiness
- GDPR & AI Privacy Alignment
- AI Policy & Regulatory Framework Development
EU AI Act Compliance & Readiness
Assessment of organizational readiness against EU AI Act requirements, gap analysis across high-risk AI systems, and development of actionable compliance roadmaps with clear milestones and ownership.
GDPR & AI Privacy Alignment
Evaluation of AI systems against data protection requirements — including data minimization, purpose limitation, automated decision-making (Article 22), and Data Protection Impact Assessments (DPIAs) specific to AI use cases.
AI Policy & Regulatory Framework Development
Drafting and operationalization of internal AI policies, acceptable use guidelines, and regulatory response protocols — ensuring alignment between legal, compliance, and AI teams.
Operationalize AI governance and drive sustainable adoption
Measure success, enable oversight and embed AI capabilities across the organization
We support organizations in setting up AI governance operating models. We help define KPIs to track rollout and maturity, select AI governance platforms, and design adoption and training programmes to ensure AI governance is embedded and effective across the organization.
Our services include:
- Responsible AI Adoption & Change Management
- AI Capability Building & Culture
- Performance, Bias & Drift Monitoring
- Ongoing Oversight & Reporting
Responsible AI Adoption & Change Management
Structured support for AI rollout across the organisation — including stakeholder alignment, change management, responsible use training, and awareness programmes tailored to different roles.
AI Capability Building & Culture
Development of AI literacy and responsible AI skills across business lines, leadership, and technical teams — from executive awareness sessions to hands-on responsible AI workshops.
Performance, Bias & Drift Monitoring
Design and implementation of continuous monitoring frameworks to track AI system performance, detect model drift, and identify bias post-deployment — enabling timely intervention before issues escalate.
Ongoing Oversight & Reporting
Establishment of ongoing AI oversight mechanisms — including dashboards, KPIs, periodic reviews, and management reporting — to maintain visibility and accountability over deployed AI systems.
Responsible AI = a more sustainable strategy
It’s not just the fact that legislation and regulations are constantly changing which makes Responsible AI important – there is also a growing demand for labour-saving technology. AI can help your company work in a more sustainable way. At the same time, Al comes with risks as applications operate with less and less human supervision. ‘Responsible AI’ is all about creating trust. Your clients are used to some services being provided by people so it’s essential you explain to them how the results of algorithms are set and that this is done in a secure way.
PwC Toolkit for security and ethics
As a company you have to comply with changing legislation and regulations, including the new EU AI Act. This makes it vital to integrate your AI solutions in a secure and accountable way. This can be achieved with our Responsible AI Toolkit, a series of customised frameworks, tools and processes that mainly focus on the security and ethics of your AI systems.
Responsible AI in action: client zero
We are our own client zero—transforming every part of our business so we can better transform yours.
For us, responsible AI is human-led and tech-powered. We’re putting the transformational power of generative AI directly in the hands of our people and our clients, embedding it into our tools and capabilities to drive measurable outcomes—while staying grounded in ethical, responsible use. As part of this commitment, we are getting our company certified for ISO/IEC 42001, aligning our AI practices with a globally recognized AI management standard.
Want to see what responsible AI looks like in practice?
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